Air Quality Management Via the Forecasting Models

Abstract

The paper addresses the possible applications of air pollution forecasting models for supporting decisions concerning regional strategy of emission abatement or the real-time emission control. The approach is based on the integration of a dynamic, air pollution forecasting model with the respective optimization techniques. The first problem (static optimization) consists in the optimal selection of emission reduction technologies within a given set of power plants. The second problem is formulated as on-line minimization of an environmental cost function, by the respective modification of emission level in the controlled sources, according to the changing meteorological conditions. The formulation of the gradient optimization algorithm is based on the necessary optimality conditions for the problem. The test computations have been performed for the above tasks, basing on the set of the major power plants in the industrial region of Upper Silesia (Poland).